Multi-criteria search procedure for trainable processors

ABSTRACT

In the execution mode of a trained processor, query key functions are compared with reference key functions stored in a memory array to select a desired response. During the comparison operation, a criterion is imposed to indicate when reference key functions corresponding to a given group of trained responses can not be an appropriate response for an encountered untrained point, wherein an untrained point is a query key for which no corresponding reference key exists. In response, search of some stored reference key functions is waived. In the multi-criteria search procedure of this invention a plurality of criteria may be imposed in an expanded search operation to waive search of specific stored reference key functions.

United States Patent 1191 1111 3,715,730

Smith et a1. 1451 Feb. 6, 1973 541 MULTI-CRITERIA SEARCH 3,446,950 5/1969 King, Jr. et al. ...............340/172.s x PROCEDURE FOR TRAINABLE 3,548,385 12 1970 Tunis ..340 172.5 PROCESSORS Primary Examiner-Paul J. Henon [75] Inventors: Stanley L. Smith, Richardson; Wil- AssismmEmml-ner Melvin chopnick Qhflale, Dallas; Michael Attorney-Samuel M. Mims, .lr., James 0. Dixon, An- Maslen Richardson, 0f drew M. Hassell, Harold Levine, Rene E. Grossman [73] Assignee: Texas Instruments Incorporated, and James Tcomfort Dallas, Tex.

ABSTRACT [22] Filed: June 1970 In the execution mode of a trained processor, query {21] App]. No.: 42,431 key functions are compared with reference key functions stored in a memory array to select a desired response. During the comparison operation, a

[52] U.S.Cl ..340/l72.5 criterion is imposed to indicate when reference key {51] Int.Cl ..G06f 15/40 functions corresponding to a given group of trained {58] Field of Search ..340/172.5, 146.3 responses can not be an appropriate response for an encountered untrained point, wherein an untrained [56] Relermces Clad point is a query key for which no corresponding UNITED STATES PATENTS reference key exists. In response, search of some stored reference key functions is waived. In the multi- R26,919 6/1970 Hagelbarger etal. ..340/172.5 criteria search procedure of this invention a plurality 3,319,229 5/1967 Fuhr et a1. 3,074,050 1/1963 Shultz 3,191,149 6/1965 Andrews.

...... ..340/172.5 of criteria may be imposed in an expanded search X operation to waive search of specific stored reference x key functions.

3,309,674 3/1967 Lemay ..340/172.5 3,440,617 4/ 1969 Lesti ..340/172.5 8 Claims, 32 Drawing Figures LEVEL 1 2 3 4 EXECUTION KEY 2425 IDIF=1 2D|F=3 ID1F=4 4DlF=5 $15 DIF=4 3D|F=2 IODIFiIO 4 5 DIF=3 PATENTEDFEB 61973 3.715.730

SHEET DSDF 20 VAL ADP VAL ADP VAL ADP G A --|o|---||2 |3 --z,|

F/g.6. VAL ADP VAL ADP VAL ADP G A i VAL ADP VAL ADP G A 9 ---|22 46---Z VAL ADP VAL ADP VAL ADP G A |o|--u5-|3-z| (D J (D VALADP VALADP G A l2 s 4 s z F/gn8. J 2

VAL ADP VAL ADP s A Lw l3 2 a 9 ----z VAL ADP VAL ADP VAL ADP G A -|Q H 5 3 -Z| I F W. ADP VAL ADP G A I2 8 4 s 2 Fig.9. QM": 6

I VAL ADP VAL ADP G A I3 2 u 2 @MJ VAL ADP G A ns 9 ---z+z 2 4 5| PAIENIEUFEB 6 I973 Fig. [0

SIIEEI 0 8 HF INITIALI ZATION SET ALL ID O IC= 0 SET VALUE OF N HEAD INPUT SIGNAL IS) AND DESIRED OUTPUT I I QUANTIZE SIGNALS I LEVEL= I IDUM=I LEVEL N mum mum I LEVEL LEVEL I ID II, IDUMI g IXILEVELI UNTRAINED POINT ID (2,ICI=IDI2,IDUMI lIDUM=IDI2JDUMI IDII,IDUMI IDII ID (2,1DUMI IDIZ, IDUM)+ I XDUMH- 2 A X=IDII,IDUMI ID(2,IDUMI LEVEL LEV IC IC+ I ID (I, ICI= IXILEVELI IDI2,ICI=1DUM ELI-I PATENTEDFEB 6 I973 3.715.730

SHEET DVUF 20 VALADPADF N VAL ADPADF N VAL ADP s A -l I 2 J 2 3 HI 3 2 I (D (7) Fig.

VAL ADPADF N VAL ADP ADF N VALADP G A I l 2 2 1- 4 3 I I 3 2 l G) l I L LVAL ADPADF N VALADP G A H'gI/Z I2 2 5 I 4 s 2 I VAL ADPADF N VAL ADP ADF N VAL ADP G A -I I 2 3 II 4 3 I r! 3 2 l (D I v J C3) LVAL ADP ADF N VAL ADP G A Fig./3 I2 2 5 2 4 5 2 I VAL ADPADF N VAL ADPADF N VAL ADP G A |l23I--I2452 l3Z VAL ADP ADF N AL ADP G A II 2 3 I 4 e 2 I F/g./4 I I VAL ADP G A PATENTEDFEB 51973 3.715 730 SHEET UBUF 20 W. ADPADF N vAI ADPADF N VAL ADP s H +||24I |2452I '|3Z|| L I l C? VALADPADF N AI. ADP s H ll 7 3 l 4 6 2 l lg. 5 4 I L I VAL ADP ADF N VAL ADP s A l3 2 8 l 5 5 Z3 l 7 VAL ADP e A a a 2 I vAI. ADPADF N VAL ADP ADF N vAI ADP s A -|I25| I2452-I3z m. ADP ADF N VAL ADP G A ll 7 3 I 4 s 2 I F/g./6 J I (5 I VAL ADPADF N VAL ADP s A I3 8 I 5 5 2 I Q) I I 5;

VAL ADPADF N LVAL ADP s A (-515 I0 I 8 8 2 I VAL ADP s A 6 l2 I0 Z I PATENTEDFEB 61973 3,715,730

SHEET DSUF 2O VALADP ADF N VAL ADPADF N VAL ADP G A I l 2 6 l2 4 5 2 3 Z I (D L J I VAL ADPADF N VAL ADP G A n 7 3 4 6 2 F/g,/7 @5 I L J VAL ADD ADF N VAL ADP G A VAL ADPADF N VAL ADP G A 65 I5 2 IO 2 a s 2 VALADP G A l2 IO 2 VAL ADPADF N VAL ADP ADF N VAL ADP G A VAL ADP ADF N LVAL ADP G A *IS 7 l0 2 4 6 2 F/g,/8 4 1 I J VAL ADP ADF N VAL ADT G A CD 1 I VAL ADPADF N VAL ADP G A ll 2 3 I 8 B Z4 I VAL ADT G A Z l2 IO 5 PATENTEDFEB ems 3.715.730

sum mar 20 REG. REG.

OUANTIZER OUANTIZER SET: 3 LEVEL'I IDUM-l IOU, IDUM) COMPARATOR IX( LEVEL) 10(2 IDUM) 7 COMPARATOR 30 LEVEL REG. 277

COMPARATOR 276 N REG.

PATENIEOM 51m 3.715.730

sum lSUF 20 IDUM REGISTER IC REGISTER ID($,[C,8|1DUM) I KEY O i I COMPONENT 308 252 255 AND G INPUT OUTPUT SELECT MATRX SELECT STORAGE I l ADP AND MATRIX |NPUT OUTPUT SELECT STORAGE SELEC T SHEET 18 0F mucoumc wvm PATENTEDFEB 61973 SHEET 1 7 [1F 7 4m o-mmr nmsmm IIyg PATENTEDFEB ems 3.715.730

SHEET 1908- 20 COMPARE COMPARE COMPARE I TOTAL COMPARE 2 COMPARE DIVIDER 2 OUTPUT SELECT SELECT I I v--- 4070 KAI 406 f OUTPUT SELECT INPUT SELECT OUTPUT SELECT J COMPARE r OUTPUT I SELECT COMPARE Fig. 27 

1. The method of operating an automatic trained processor apparatus beyond a trained point with an untrained point where said automatic trained processor is trained to produce trained responses to query sets of input signals, said automatic trained processor apparatus including a memory array with reference sets of signals stored along with corresponding trained responses forming a data base to locate and extract a desired response to query sets of signals forming an untrained point, comprising the steps of: a. searching in said automatic trained processor apparatus through the reference sets stored in the memory array with a query set forming said untrained point, b. selecting in said automatic trained processor apparatus a plurality of reference sets from said memory array according to a first predetermined criterion, and c. selecting in said automatic trained processor apparatus from the trained responses corresponding to said plurality of selected reference sets, a desired output for said untrained point according to a second predetermined criterion.
 1. The method of operating an automatic trained processor apparatus beyond a trained point with an untrained point where said automatic trained processor is trained to produce trained responses to query sets of input signals, said automatic trained processor apparatus including a memory array with reference sets of signals stored along with corresponding trained responses forming a data base to locate and extract a desired response to query sets of signals forming an untrained point, comprising the steps of: a. searching in said automatic trained processor apparatus through the reference sets stored in the memory array with a query set forming said untrained point, b. selecting in said automatic trained processor apparatus a plurality of reference sets from said memory array according to a first predetermined criterion, and c. selecting in said automatic trained processor apparatus from the trained responses corresponding to said plurality of selected reference sets, a desired output for said untrained point according to a second predetermined criterion.
 2. The method claimed in claim 1 wherein said first criterion is a predetermined threshold between the query set and the reference set.
 3. The method claimed in claim 1 wherein said second criterion is the trained response corresponding to the reference set having a minimum Hamming distance between the query set and the reference set.
 4. The method claimed in claim 1 wherein said first criterion is when the query set and the reference set differ by a predetermined threshold and the second criterion is when the reference set having the desired trained response differs from the query set by a minimum Hamming distance.
 5. The method claimed in claim 1 wherein said first criterion is determined by the number of bits of information in a subarray past a predetermined threshold.
 6. An automatic processor trained to produce trained responses to query sets of input signals, said processor comprising: a. a memory array for storing reference sets of signals along with corresponding trained responses, b. comparison means responsive to a query set of signals not encountered in training constituting an untrained point to compare said query set, component by component, with said reference sets of signals, c. means for storing the difference function resulting from the comparison of said query set to said reference sets by said comparison means, d. means for storing the difference function resulting from the total comparison between said query set and said reference sets, e. means for accumulating the difference function resulting from the comparison of each component of said query set with each component of said reference sets, f. means for comparing the stored total difference function and the accumulated difference function, g. means responsive to the comparison of said total difference function and said accumulated difference function to waive further comparison of the reference sets being compared when the accumulated difference exceeds the total difference function, h. means for establishing a predetermined threshold, i. means for comparing the difference function resulting from the comparison of each component with said threshold, and j. means responsive to the comparison of said difference function for each component with said predetermined threshold for waiving further comparison of the rest of the sets being compared when said difference function for a component exceeds said predetermined threshold.
 7. The method of claim 1 wherein said reference sets and said trained responses are stored in a tree allocated file in said memory array. 